Marijke Welvaert

On the definition of signal-to-noise ratio and contrast-to-noise ratio for FMRI data.

Signal-to-noise ratio, the ratio between signal and noise, is a quantity that has been well established for MRI data but is still subject of ongoing debate and confusion when it comes to fMRI data. fMRI data are characterised by small activation fluctuations in a background of noise. Depending on how the signal of interest and the noise are identified, signal-to-noise ratio for fMRI data is reported by using many different definitions. Since each definition comes with a different scale, interpreting and comparing signal-to-noise ratio values for fMRI data can be a very challenging job. In this paper, we provide an overview of existing definitions. Further, the relationship with activation detection power is investigated. Reference tables and conversion formulae are provided to facilitate comparability between fMRI studies.

Low carbohydrate, high fat diet impairs exercise economy and negates the performance benefit from intensified training in elite race walkers

Three weeks of intensified training and mild energy deficit in elite race walkers increases peak aerobic capacity independent of dietary support. Adaptation to a ketogenic low carbohydrate, high fat (LCHF) diet markedly increases rates of whole‐body fat oxidation during exercise in race walkers over a range of exercise intensities. The increased rates of fat oxidation result in reduced economy (increased oxygen demand for a given speed) at velocities that translate to real‐life race performance in elite race walkers. In contrast to training with diets providing chronic or periodised high carbohydrate availability, adaptation to an LCHF diet impairs performance in elite endurance athletes despite a significant improvement in peak aerobic capacity.

Graded Effects of Number of Inserted Letters in Superset Priming

Three masked priming experiments investigated the effects of target word length and number of inserted letters on superset priming, where irrelevant letters are added to targets to form prime stimuli (e.g., tanble-table). Effects of one, two, three, and four-letter insertions were measured relative to an unrelated prime condition, the identity prime condition, and a condition where the order of letters of the superset primes was reversed. Superset primes facilitated performance compared with unrelated primes and reversed primes, and the overall pattern showed a small cost of letter insertion that was independent of target word length and that increased linearly as a function of the number of inserted letters. A meta-analysis incorporating data from the present study and two other studies investigating superset priming, showed an average estimated processing cost of 11 ms per letter insertion. Models of letter position coding are examined in the light of this result.

A Review of fMRI Simulation Studies

Simulation studies that validate statistical techniques for fMRI data are challenging due to the complexity of the data. Therefore, it is not surprising that no common data generating process is available (i.e. several models can be found to model BOLD activation and noise). Based on a literature search, a database of simulation studies was compiled. The information in this database was analysed and critically evaluated focusing on the parameters in the simulation design, the adopted model to generate fMRI data, and on how the simulation studies are reported. Our literature analysis demonstrates that many fMRI simulation studies do not report a thorough experimental design and almost consistently ignore crucial knowledge on how fMRI data are acquired. Advice is provided on how the quality of fMRI simulation studies can be improved.

Behavioural treatment strategies improve adherence to lifestyle intervention programmes in adults with obesity: a systematic review and meta-analysis

Poor adherence to lifestyle intervention remains a key factor hindering treatment effectiveness and health outcomes for adults with obesity. The aim of this systematic review and meta‐analysis is to determine if behavioural treatment strategies (e.g. goal setting, motivational interviewing, relapse prevention, cognitive restructuring etc.) improve adherence to lifestyle intervention programmes in adults with obesity. Randomized controlled trials that investigated the use of behavioural treatment strategies in obesity management were identified by systematically reviewing the literature within Medline, PsycINFO, CINAHL, SPORTDiscus and Web of Science from their inception to August 2016. This meta‐analysis shows that behavioural treatment interventions have a significant positive effect on session attendance (percentage) and physical activity (total min/week) in adults with obesity (Mu2009=u200917.63 (95% confidence interval (CI) = 10.77, 24.50), z =5.0337, P < 0.0001 and Mu2009=u2009105.98 (95% CI = 58.64, 153.32), z =4.3878, P < 0.0001, respectively). This meta‐analysis of randomized controlled trials provides evidence that behavioural treatment strategies improve adherence to lifestyle intervention programmes in adults with obesity. These strategies should be routinely incorporated into lifestyle intervention, obesity management and weight loss programmes with the aim of improving engagement and adherence. If adherence were improved, treatment effectiveness, health outcomes and the ultimate burden of chronic disease could also be improved.

Effect of Environmental and Feedback Interventions on Pacing Profiles in Cycling: A Meta-Analysis

In search of their optimal performance athletes will alter their pacing strategy according to intrinsic and extrinsic physiological, psychological and environmental factors. However, the effect of some of these variables on pacing and exercise performance remains somewhat unclear. Therefore, the aim of this meta-analysis was to provide an overview as to how manipulation of different extrinsic factors affects pacing strategy and exercise performance. Only self-paced exercise studies that provided control and intervention group(s), reported trial variance for power output, disclosed the type of feedback received or withheld, and where time-trial power output data could be segmented into start, middle and end sections; were included in the meta-analysis. Studies with similar themes were grouped together to determine the mean difference (MD) with 95% confidence intervals (CIs) between control and intervention trials for: hypoxia, hyperoxia, heat-stress, pre-cooling, and various forms of feedback. A total of 26 studies with cycling as the exercise modality were included in the meta-analysis. Of these, four studies manipulated oxygen availability, eleven manipulated heat-stress, four implemented pre-cooling interventions and seven studies manipulated various forms of feedback. Mean power output (MPO) was significantly reduced in the middle and end sections (p < 0.05), but not the start section of hypoxia and heat-stress trials compared to the control trials. In contrast, there was no significant change in trial or section MPO for hyperoxic or pre-cooling conditions compared to the control condition (p > 0.05). Negative feedback improved overall trial MPO and MPO in the middle section of trials (p < 0.05), while informed feedback improved overall trial MPO (p < 0.05). However, positive, neutral and no feedback had no significant effect on overall trial or section MPO (p > 0.05). The available data suggests exercise regulation in hypoxia and heat-stress is delayed in the start section of trials, before significant reductions in MPO occur in the middle and end of the trial. Additionally, negative feedback involving performance deception may afford an upward shift in MPO in the middle section of the trial improving overall performance. Finally, performance improvements can be retained when participants are informed of the deception.

A multifactorial evaluation of illness risk factors in athletes preparing for the Summer Olympic Games

OBJECTIVESnIllness can disrupt training and competition performance of athletes. Few studies have quantified the relative contribution of the known medical, behavioural and lifestyle risk factors.nnnDESIGNnCross-sectional.nnnMETHODSnOlympic athletes from 11 sports (n=221) were invited to complete questionnaires administered nine months before the Rio 2016 Olympic Games. These included the Depression, Anxiety and Stress Questionnaire (DASS-21), Perceived Stress Scale (PSS), Dispositional Resilience Scale (DRS), Recovery-Stress Questionnaire (REST-Q-52 item), Low Energy in Females Questionnaire (LEAF-Q), a modified Personal and Household Hygiene questionnaire, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, and custom-made questionnaires on probiotic usage and travel. An illness (case) was defined as an event which limited training or competition for greater hours in the prior month. Odds ratios and attributable fractions in the population (AFP) were utilised for categorical variables with independent t-tests or Wilcoxon rank-sum for continuous variables.nnnRESULTSnEighty-one athletes responded (male, n=26; female, n=55). There were 16 illness cases and 65 controls. Female athletes were at higher odds of illness (OR=9.4, 95%CI 1.3-410, p=0.01, AFP=0.84). Low energy availability (LEAF-Q score ≥8: OR=7.4, 95%CI 0.78-352, p=0.04, AFP=0.76), depression symptoms (DASS-21: depression score >4, OR=8.4, 95%CI 1.1-59, p<0.01; AFP=0.39) and higher perceived stress (PSS: 10-item, p=0.04) were significantly associated with illness.nnnCONCLUSIONSnFemale sex, low energy availability, and mental health are associated with sports incapacity (time loss) due to illness. Low energy availability had high attributable fractions in the population and stands out as a primary association with illness.

How ignoring physiological noise can bias the conclusions from fMRI simulation results

Neuroimaging researchers use simulation studies to validate their statistical methods because it is acknowledged that this is the most feasible way to know the ground truth of the data. The noise model used in these studies typically varies from a simple Gaussian distribution to an estimate of the noise distribution from real data. However, although several studies point out the presence of physiological noise in fMRI data, this noise source is currently lacking in simulation studies. Therefore, we explored the impact of adding physiological noise to the simulated data. For several experimental designs, fMRI data were generated under different noise models while the signal-to-noise ratio was kept constant. The sensitivity and specificity of a standard statistical parametric mapping (SPM) analysis were determined by comparing the known activation with the detected activation. We show that by including physiological noise in the data generation process, the simulation results in terms of sensitivity and specificity drop dramatically. Additionally, we used the new proposed simulation model to compare a standard SPM analysis against the method proposed by Cabella et al. (2009). The results indicate that the analysis of data containing no physiological noise yields a better performance of the SPM analysis. However, if physiological noise is included in the data, the sensitivity and specificity of the Cabella method are higher compared to the SPM analysis. Based on these results, we argue that the results of current simulation studies are likely to be biased, especially when analysis methods are compared using ROC curves.

Prevalence of illness, poor mental health and sleep quality and low energy availability prior to the 2016 Summer Olympic Games

Objective Establish the prevalence of illness symptoms, poor sleep quality, poor mental health symptoms, low energy availability and stress-recovery state in an Olympic cohort late in the 3u2009months prior to the Summer Olympic Games. Methods Olympic athletes (n=317) from 11 sports were invited to complete questionnaires administered 3u2009months before the Rio 2016 Olympic Games. These questionnaires included the Depression, Anxiety and Stress Questionnaire, Perceived Stress Scale, Dispositional Resilience Scale, Recovery-Stress Questionnaire (REST-Q-52 item), Low Energy Availability in Females Questionnaire (LEAF-Q), Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index and custom-made questionnaires on probiotic usage and travel. Multiple illness (case) definitions were applied. ORs and attributable fractions in the population were used. Factor analyses were used to explore the relationships between variables. Results The response rate was of 42% (male, n=47, age 25.8±4.1u2009years; female, n=85, age 24.3±3.9u2009years). Low energy availability was associated with sustaining an illness in the previous month (upper respiratory, OR=3.8, 95%u2009CI 1.2 to 12). The main factor relating to illness pertained to a combination of anxiety and stress-recovery states (as measured by the REST-Q-52 item). All participants reported at least one episode of illness in the last month (100% prevalence). Conclusions All participants reported at least one illness symptom in the previous month. Low energy availability was a leading variable associated with illness in Olympic-class athletes. The estimates duration of symptoms ranged from 2 to 7 days. Factor analyses show the interdependence of various health domains and support multidisciplinary care.

The effects of football match congestion in an international tournament on hip adductor squeeze strength and pain in elite youth players

ABSTRACT The purpose of this study was to investigate the effect of a congested international tournament match schedule on adductor strength and pain in elite youth football players. Twenty-two male players (age: 15.53 ± 0.48 years, height: 174.87 ± 7.59 cm, weight: 67.45 ± 7.40 kg) were included. The 5-second adductor squeeze strength was captured daily using a hand-held dynamometer during a 7-game international tournament. Pain during the squeeze test was recorded using numerical pain ratings (0–10) to quantify groin pain. Sessional rate of perceived exertion (sRPE) was collected during the tournament. Adductor strength changed significantly during the tournament in relation to time (F(14,294.94) = 1.89, p = 0.027) and cumulative sRPE (F(1,314) = 5.59, p = 0.019). Cumulative sRPE displayed a negative relationship with strength (B = −0.008, SE = 0.0032, 95%CI = −0.014,-0.002). The results indicate that for every 100 match sRPE arbitrary units the squeeze peak force reduced by 0.8N. Sixteen (72.7%) players demonstrated clinically meaningful strength reductions (>15%) during the tournament. Match congestion impacts on hip adductor squeeze strength in male youth football players. A negative relationship between match sRPE and adductor strength exists. Player monitoring involving the 5-second adductor squeeze test can be captured effectively and is suitable to include as part of secondary injury prevention during or immediately after a congested tournament.